SharePoint can be either your best “single source of truth”… or the reason your refreshes fail on Monday morning. This guide shows how to structure SharePoint properly (sites, libraries, lists), set permissions that scale, and connect everything cleanly to Excel  and Power BI —with practical “do this / don’t do that” patterns. PRACTICE MATERIAL BELOW! Check out some of our FREE templates and materials. 1) SharePoint basics that matter for BI people Sites, Libraries, Lists (t

If you’ve ever wanted cleaner dashboards, faster “at-a-glance” reading, and less “wall of numbers” fatigue—Unicode symbols + hex colors are a surprisingly powerful combo. In this post you’ll learn practical, copy-paste-ready tricks for Excel , Power BI (DAX + conditional formatting) , and Power Query . PRACTICE MATERIAL BELOW! Check out some of our FREE templates and materials. Why this matters (real-life use cases) Status columns that actually read well : ✅ OK, ⚠ Warning, ❌

Introduction Ever wondered what happens behind the scenes when you drag a visual into Power BI? That’s DAX queries  at work. While most users write DAX formulas  to calculate measures or columns, DAX queries  go one level deeper — they let you directly query your model, test logic, and debug calculations.In this post, we’ll break down what DAX queries are, how they work, their structure, examples, pitfalls, and best practices — plus a few pro tricks to level up your Power BI

Overview When you connect Power Query / Power BI to a SharePoint site (or document library), there are (at least) two common M-functions you may see or use: SharePoint.Files(siteUrl as text, optional options as record) as table SharePoint.Contents(siteUrl as text, optional options as record) as table Although they sound similar, their behavior, performance, metadata returned, and navigation experience differ. Understanding their differences helps in building more robust and p

Hook:  If your model “mysteriously” changes numbers, breaks relationships, or sorts months alphabetically—blame data types. What we’ll cover:  where to define types (and why), the safest order of operations across the ETL chain, Power Query vs. Model vs. Table View, special cases (DirectQuery, currency, duration), and concrete, copy-paste examples. 1) Why data types matter (and where they live) Power Query (PQ):  Data shaping stage. Types here affect folding, transformations

If you’re already familiar with Power BI  and Power Automate , you know how powerful it is when these two tools work together. But one of the most game-changing triggers  in Power Automate is: 👉 “Run a query against a dataset” This trigger lets you execute DAX queries (Data Analysis Expressions)  directly against your Power BI dataset from a flow. That means you can extract aggregated results, row-level values, or KPIs in real time — and then use that information to trigger

Hook:  Hard-coded paths are silent project killers. Move a file, share a workbook, or publish a PBIX—and boom: refresh fails. Goal:  In ~10 minutes you’ll set up robust, parameter-driven paths for Excel (Power Query) and Power BI (Desktop & Service), plus a tiny, reusable M pattern you can paste into any project. 1) Why hard-coded paths fail When you embed "C:\Users\Alice\Project\data.csv" in a query, anyone whose files live elsewhere (e.g., D:\Work\Data\) will get errors. I

Microsoft Power BI Desktop  contains a rich set of modelling and reporting features, yet many power users enhance their workflow with external tools . These tools attach to the Analysis Services instance behind a PBIX/Power BI semantic model and allow advanced editing, scripting, performance analysis and automation. The External Tools  ribbon lists all registered tools, and Microsoft warns that these are produced by independent developers; editing metadata outside Power BI De

Introduction Building effective Power BI reports is not just about loading data and creating visuals—it’s about structuring your data model correctly. Relationships are at the heart of that structure. In this post, we’ll explore what relationships in Power BI are, why they matter, how to create and manage them, and some advanced tricks to avoid common pitfalls. Understanding Relationships in Power BI Relationships define how tables connect with each other. Without them, your

If you're a moderately experienced Power BI user, you’ve likely encountered the CALCULATE  function in DAX (Data Analysis Expressions)....

Excel users often seek efficient ways to retrieve data from large spreadsheets. Two powerful functions that stand out in this pursuit are...

Goal:  a fast, self-updating Power BI report that tracks earthquakes in the European–Mediterranean region (with a global table for comparison), highlights activity hotspots, and surfaces clean KPIs for decision-making. Scope: Earthquakes in the European-Mediterranean region with magnitude 4.5 or greater within the last 720 days or the last 2 years. Source: ETH Zürich - Swiss Seismological Service (HTML daily data): http://www.seismo.ethz.ch/en/earthquakes/europe/last90daysMa

Power BI’s Power Query (M language) allows creating custom functions and reusable query steps to simplify common tasks. Below are five...

Want faster refreshes and snappier previews? Here’s a practical, no-nonsense guide to making Power Query load much  quicker using only...

This post walks through the exact setup shown in your screenshots: folder-based CSV ingestion in Power Query, a tidy star schema, an FX...

Power BI is a powerful business intelligence tool. The DAX (Data Analysis Expressions) language allows users to create custom...

Imagine spending hours perfecting your Power BI reports, only to struggle when trying to present them clearly to your stakeholders or...

Have you ever received an email with a link to download a CSV or Excel file, and wished it could just go straight into your Excel sheet...

When you're transforming data in Power BI or Excel using Power Query, you're bound to run into errors —mismatched data types, division by text, nulls, you name it. But instead of manually inspecting row by row, why not automate error detection with a custom Power Query function ? In this blog post, I’ll walk you through a clean method to catch and analyze all row-level errors  using Power Query. This approach works great when importing or transforming large datasets. We’ll co

Power BI's secret sauce is DAX (Data Analysis Expressions)  – a formula language that lets you create dynamic calculations and advanced...